FlappyLearning and FlappyBirdRL
These are competitors—both implement different machine learning approaches (neuroevolution vs. reinforcement learning) to solve the identical problem of training an AI agent to play Flappy Bird autonomously.
About FlappyLearning
xviniette/FlappyLearning
Program learning to play Flappy Bird by machine learning (Neuroevolution)
This program helps demonstrate how machine learning can tackle simple control tasks in games. It takes the game state (like the bird's position and upcoming pipes) and, through an evolutionary process, learns to output the optimal 'flap' or 'no flap' action. This is primarily for developers, educators, or students interested in seeing neuroevolution in action within a game context.
About FlappyBirdRL
SarvagyaVaish/FlappyBirdRL
Flappy Bird hack using Reinforcement Learning
This project explores how a computer can learn to play the game Flappy Bird on its own. It takes information about the game state, like the bird's position and upcoming obstacles, and outputs decisions on when to 'flap.' This is ideal for anyone interested in seeing fundamental reinforcement learning concepts applied to a simple game.
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